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ENSURING QUERY INTEGRITY FOR SPATIAL DATA IN THE CLOUD
by
Ling Hu
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(COMPUTER SCIENCE)
December 2012
Copyright 2012 Ling Hu

With the popularity of location-based services (LBS) and the abundant usage of smart phones, tablets and other GPS-enabled devices, the necessity of providing efficient, reliable and cost-effective spatial data services has grown rapidly over the past few years. Consequently, outsourcing reduce the cost of managing and maintaining databases in-house but maintaining the same quality-of-service to their clients. Meanwhile, the fast arising trend of Cloud storage and Cloud computing services has provided a flexible and cost-effective platform for hosting data from businesses and individuals, further enabling many location-based applications. Nevertheless, in this new database outsourcing paradigm, how to ensure the integrity of the query results for the clients remains a challenging problem. ❧ To address the query integrity problem, we propose a new framework, named VNAuth, which allows a client to verify the correctness and completeness of the result set retrieved from the Cloud using spatial neighborhood information derived from the Voronoi diagram of the underlying dataset. VNAuth handles not only fundamental spatial query types, such as k-nearest-neighbor and range queries, but also more advanced query types like reverse k nearest neighbors, k aggregate nearest neighbors, and spatial skylines. Furthermore, we show that VNAuth can be extended from the Euclidean space to road networks where objects can only move on pre-defined trajectories, enabling spatial network query integrity. We evaluated VNAuth based on real-world datasets using mobile devices (Google Droid smart phones with Android OS) as query clients. Compared to the current state-of-the-art approaches (i.e., methods based on Merkle hash trees), our experiments show that VNAuth produces significantly smaller verification objects and is more computationally efficient, especially for queries with low selectivity.

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ENSURING QUERY INTEGRITY FOR SPATIAL DATA IN THE CLOUD
by
Ling Hu
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(COMPUTER SCIENCE)
December 2012
Copyright 2012 Ling Hu